internal/ceres/tiny_solver_autodiff_function_test.cc

// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2017 Google Inc. All rights reserved.
// http://ceres-solver.org/
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// Author: mierle@gmail.com (Keir Mierle)

#include "ceres/tiny_solver_autodiff_function.h"

#include <algorithm>
#include <cmath>
#include <limits>

#include "gtest/gtest.h"

namespace ceres {

typedef Eigen::Matrix<double, 2, 1> Vec2;
typedef Eigen::Matrix<double, 3, 1> Vec3;

struct AutoDiffTestFunctor {
  template<typename T>
  bool operator()(const T* const parameters, T* residuals) const {
    // Shift the parameters so the solution is not at the origin, to prevent
    // accidentally showing "PASS".
    const T& a = parameters[0] - T(1.0);
    const T& b = parameters[1] - T(2.0);
    const T& c = parameters[2] - T(3.0);
    residuals[0] = 2.*a + 0.*b + 1.*c;
    residuals[1] = 0.*a + 4.*b + 6.*c;
    return true;
  }
};

// Leave a factor of 10 slop since these tests tend to mysteriously break on
// other compilers or architectures if the tolerance is too tight.
static double const kTolerance = std::numeric_limits<double>::epsilon() * 10;

TEST(TinySolverAutoDiffFunction, SimpleFunction) {
  typedef TinySolverAutoDiffFunction<AutoDiffTestFunctor, 2, 3>
      AutoDiffTestFunction;
  AutoDiffTestFunctor autodiff_test_functor;
  AutoDiffTestFunction f(autodiff_test_functor);

  Vec3 x(2.0, 1.0, 4.0);
  Vec2 residuals;

  // Check the case with cost-only evaluation.
  residuals.setConstant(555);  // Arbitrary.
  EXPECT_TRUE(f(&x(0), &residuals(0), NULL));
  EXPECT_NEAR(3.0, residuals(0), kTolerance);
  EXPECT_NEAR(2.0, residuals(1), kTolerance);

  // Check the case with cost and Jacobian evaluation.
  Eigen::Matrix<double, 2, 3> jacobian;
  residuals.setConstant(555);  // Arbitrary.
  jacobian.setConstant(555);
  EXPECT_TRUE(f(&x(0), &residuals(0), &jacobian(0, 0)));

  // Verify cost.
  EXPECT_NEAR(3.0, residuals(0), kTolerance);
  EXPECT_NEAR(2.0, residuals(1), kTolerance);

  // Verify Jacobian Row 1.
  EXPECT_NEAR(2.0, jacobian(0, 0), kTolerance);
  EXPECT_NEAR(0.0, jacobian(0, 1), kTolerance);
  EXPECT_NEAR(1.0, jacobian(0, 2), kTolerance);

  // Verify Jacobian row 2.
  EXPECT_NEAR(0.0, jacobian(1, 0), kTolerance);
  EXPECT_NEAR(4.0, jacobian(1, 1), kTolerance);
  EXPECT_NEAR(6.0, jacobian(1, 2), kTolerance);
}
}  // namespace tinysolver